Mistral Medium vs o4-mini: API Cost Comparison
Compare the API pricing, context windows, features, and real-world cost projections for Mistral Medium (Mistral AI) and o4-mini (OpenAI). Use the interactive calculator below to compute your exact monthly cost based on your token usage and request volume.
Prices verified Apr 30, 2026
Interactive Cost Calculator
Fills in typical token counts for a workload type
Tokens in each prompt sent to the model
Tokens generated in each response
Total API calls per month
Showing costs for 2 models. Cheapest: o4-mini at $33.00/month.
| Alert | |||||||
|---|---|---|---|---|---|---|---|
Besto4-mini | OpenAI | $33.00 | $0.003300 | $11.00 | $22.00 | 37.1% | Alerts coming soon |
Mistral Medium | Mistral AI | $52.50 | $0.005250 | $15.00 | $37.50 | — | Alerts coming soon |
Monthly Cost Comparison
Price Comparison at a Glance
All prices are in USD per 1 million tokens ($/M tokens). Lower is cheaper.
| Pricing Type | Mistral Medium | o4-mini | Cheaper |
|---|---|---|---|
| Input (standard) | $1.50/M | $1.10/M | o4-mini |
| Output | $7.50/M | $4.40/M | o4-mini |
| Cached input | N/A | $0.28/M | — |
| Batch input | N/A | $0.55/M | — |
| Batch output | N/A | $2.20/M | — |
Prices last verified: 2026-03-08 – 2026-04-30
Cost Breakdown by Usage Volume
Estimated monthly costs at different request volumes, assuming 1,000 input tokens and 500 output tokens per request. Adjust in the calculator above for your specific use case.
| Volume | Mistral MediumMonthly | o4-miniMonthly | Mistral MediumPer request | o4-miniPer request |
|---|---|---|---|---|
| 1K requests/mo | $5.25 | $3.30 | $0.005250 | $0.003300 |
| 10K requests/mo | $52.50 | $33.00 | $0.005250 | $0.003300 |
| 100K requests/mo | $525.00 | $330.00 | $0.005250 | $0.003300 |
| 1M requests/mo | $5,250.00 | $3,300.00 | $0.005250 | $0.003300 |
Green values indicate the lower-cost option at each volume tier. Cost per request is calculated at 1,000 input + 500 output tokens using standard (non-batch, non-cached) pricing.
Price History
Input price per 1M tokensWhen to Choose Mistral Medium
by Mistral AI
- General chatbot
- Customer support
- Content & copywriting
Input / 1M tokens
$1.50/M
Output / 1M tokens
$7.50/M
Context window
131,072
Tier
premium
When to Choose o4-mini
by OpenAI
- Code generation
- Data extraction
Input / 1M tokens
$1.10/M
Output / 1M tokens
$4.40/M
Context window
200,000
Tier
reasoning
Key Differences Beyond Price
Cost is only one factor in choosing an AI model. Context window size, rate limits, supported features, and latency all affect whether a model fits your use case.
| Capability | Mistral Medium | o4-mini |
|---|---|---|
| Context window | 131,072 tokens | 200,000 tokens |
| Max output tokens | 4,096 tokens | 100,000 tokens |
| Performance tier | Premium | Reasoning |
| Vision / image input | No | Yes |
| Function calling | Yes | Yes |
| JSON mode | Yes | Yes |
| Prompt caching | No | Yes |
| Batch API (50% discount) | No | Yes |
| Extended reasoning | No | Yes |
| Fine-tuning | No | No |
| Rate limit (req/min) | Not published | 1,000 |
Mistral Medium notes
Good balance of quality and cost for European GDPR-compliant workloads.
o4-mini notes
Configurable reasoning effort. Best budget reasoning model from OpenAI.
Frequently Asked Questions
Is Mistral Medium cheaper than o4-mini?
At standard usage (1,000 input tokens, 500 output tokens, 100,000 requests/month), o4-mini costs $330.00/month versus $525.00/month for Mistral Medium — a 37% saving. Your actual savings will vary based on your token profile; output-heavy workloads amplify differences in output pricing.
Which model has a larger context window, Mistral Medium or o4-mini?
o4-mini has a larger context window at 200,000 tokens, compared to 131,072 tokens for Mistral Medium. A larger context window is important for processing long documents, multi-turn conversations, or large codebases without truncation.
Do Mistral Medium and o4-mini support the Batch API?
o4-mini supports the Batch API (50% discount for async processing), while Mistral Medium does not. If your workload tolerates up to 24-hour latency, routing to o4-mini with batch pricing could significantly cut costs versus Mistral Medium's standard rate.
Which model offers better prompt caching?
o4-mini supports prompt caching at $0.28/M for cached input, while Mistral Medium does not offer prompt caching. For RAG applications or chatbots with large, repeated context, o4-mini's caching capability can substantially reduce effective costs.
What are the best use cases for Mistral Medium vs o4-mini?
Mistral Medium is best suited for General chatbot, Customer support, Content & copywriting, while o4-mini is optimized for Code generation, Data extraction. Choose based on which use case matches your primary workload — and validate with the cost calculator above to confirm the total monthly spend fits your budget.
What is the cost per request for Mistral Medium vs o4-mini?
At 1,000 input tokens and 500 output tokens per request — a typical conversational workload — Mistral Medium costs $0.005250 per request and o4-mini costs $0.003300 per request. At 100,000 requests/month, that translates to $525.00 and $330.00 respectively. Use the interactive calculator to adjust these parameters for your actual workload.
Mistral Medium vs o4-mini: Summary
When comparing Mistral Medium and o4-mini for API cost, the right choice depends on your workload's token profile, required features, and tolerance for latency. o4-mini offers lower total cost at standard usage volumes (1,000 input + 500 output tokens per request at 100,000 requests/month) at $330.00/month, compared to $525.00/month for Mistral Medium.
Both models are priced in USD per million tokens, the standard unit across all major AI API providers. Mistral Medium charges $1.50/M for input tokens and $7.50/M for output tokens. o4-mini charges $1.10/M input and $4.40/M output. If your workload is output-heavy (more tokens generated than consumed as input), the model with the lower output price compounds cost savings significantly at scale.
Prompt caching is supported by o4-mini but not Mistral Medium. For workloads with large, repeated system prompts or document context — such as RAG pipelines or multi-turn conversations with a fixed knowledge base — prompt caching can reduce effective input costs by 60–90%, which may change the cost ranking between these two models at your specific usage pattern.
Context window capacity differs between the two: o4-mini supports up to 200,000 tokens in a single request, versus 131,072 tokens for Mistral Medium. A larger context window is essential for document summarization, large codebase analysis, and multi-document retrieval-augmented generation (RAG) applications.
Use the interactive calculator at the top of this page to enter your actual token usage and monthly request volume for a precise cost comparison tailored to your workload. Adjust for batch API discounts and prompt caching to find the most cost-effective option for your specific deployment.
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